Quantitative Digital Image Analysis Research Articles

Clinicopathologic significance of the delta-like ligand 4, vascular endothelial growth factor, and hypoxia-inducible factor-2α in gallbladder cancer.

Gallbladder cancer (GBC) is usually detected in advanced stages with a low 5-year survival rate. Delta-like ligand 4 (DLL4), vascular endothelial growth factor (VEGF), and hypoxia-inducible factor-2alpha (HIF2α) have been studied for their role in tumorigenesis and potential for therapeutic target, and multiple clinical trials of the agents targeting them are ongoing. We investigated the expression of these markers in surgically resected GBC and tried to reveal their association with the clinicopathologic features, mutual correlation of their expression, and prognosis of the GBC patients by their expression. We constructed the tissue microarray blocks of 99 surgically resected GBC specimens and performed immunohistochemistry of DLL4, VEGF, and HIF2α. We used the quantitative digital image analysis to evaluate DLL4 and VEGF expression, while the expression of HIF2α was scored manually. The expression of VEGF and HIF2α showed a significant trend with tumor differentiation (p= .028 and p= .006, respectively). We found that the high DLL4 and VEGF expression were significantly correlated with lymph node metastasis (p= .047, both). The expression of VEGF and HIF2α were significantly correlated (p < .001). The GBC patients with low HIF2α expression showed shorter recurrence-free survival than those with high HIF2α expression. This study suggested the possibility of the usage of DLL4 and VEGF to predict the lymph node metastasis and the possibility of VEGF and HIF2α to predict the expression level mutually. Further studies may be needed to validate our study results and eventually accelerate the introduction of the targeted therapy in GBC.

Pathogenesis of Kasokero virus in experimentally infected Egyptian rousette bats (Rousettus aegyptiacus)

Egyptian rousette bats (ERBs; Rousettus aegyptiacus; family Pteropodidae) are associated with a growing number of bunyaviruses of public health importance, including Kasokero virus (KASV), which was first identified as a zoonosis in Uganda in 1977. In this study, formalin-fixed paraffin-embedded tissues from a previous experiment in which KASV infection was confirmed in 18 experimentally infected ERBs were used for an in-depth analysis using histopathology, in situ hybridization (ISH) for detection of viral RNA, immunohistochemistry (IHC) to assess the mononuclear phagocyte system response, and quantitative digital image analysis to investigate virus clearance from the liver and spleen within a spatial context. Significant gross and histological lesions were limited to the liver, where KASV-infected bats developed mild to moderate, acute viral hepatitis, which was first observed at 3 days postinfection (DPI), peaked at 6 DPI, and was resolved by 20 DPI. A subset of bats had glycogen depletion (n = 10) and hepatic necrosis (n = 3), rarely with intralesional bacteria (n = 1). Virus replication was confirmed by ISH in the liver, spleen, lymph nodes, and tongue. In the liver, KASV replicated in the cytoplasm of hepatocytes, to a lesser extent in mononuclear phagocytes, and rarely in presumptive endothelial cells. Most KASV RNA, as detected by ISH, was cleared from the spleen and liver by 6 DPI. It is concluded that ERBs have effective mechanisms to respond to this virus, clearing it without evidence of clinical disease.

Use of Endoscopic Scraper and Cell Block Technique as a Replacement for Conventional Brush for Diagnosing Malignant Biliary Strictures.

Simple SummaryBrush cytology remains the primary method used worldwide for diagnosing malignant biliary strictures, despite its low sensitivity. Although the endoscopic scraper, the simplicity of which is comparable to that of a conventional brush, has been used mainly in Japan, it has yet to gain popularity on a global scale. The purpose of this study was to evaluate the diagnostic performance of the endoscopic scraper by comparing diagnostic yields and the number of collected cells using quantitative digital image analysis. Our study revealed that the endoscopic scraper and cell block method achieved higher sensitivity than the brush with the cell block method, and showed that the number of cells on the cell block sections obtained by the endoscopic scraper were significantly higher than those obtained using the brush. Given its ease of use and high sample acquisition capability, the endoscopic scraper could replace brush cytology for diagnosing malignant biliary strictures.Histological evidence is essential for diagnosing malignant biliary strictures. However, conventional brush cytology remains the primary method used worldwide, despite its low diagnostic sensitivity and accuracy, as it is technically easy, rapid, and cost-effective. The aim of this study was to evaluate the diagnostic performance of a recently introduced endoscopic scraper, the simplicity of which is comparable to that of a conventional brush, by comparing diagnostic yields and the number of collected cells. The sensitivity of the endoscopic scraper when using the cell block technique was significantly higher than when using brush cytology or a brush with the cell block technique (53.6% vs. 30.9%, p < 0.001; 53.6% vs. 31.6%, p = 0.024, respectively). Quantitative digital image analysis of cell block sections revealed that the median number of cells obtained with the endoscopic scraper was significantly higher than when using the brush (1917 vs. 1014 cells, p = 0.042). Furthermore, seven cases (8.3%; 7/84) were diagnosed by immunohistochemical analysis of the cell block section obtained from the endoscopic scraper. Given its simplicity and greater capacity for sample acquisition, use of the endoscopic scraper in conjunction with the cell block technique could replace brush cytology for the histological diagnosis of malignant biliary strictures.

FRI184 - Etiology-independent fibrosis severity scoring by quantitative digital pathology image analysis

FRI184 - Etiology-independent fibrosis severity scoring by quantitative digital pathology image analysis

Progression and Dissemination of Pulmonary Mycobacterium Avium Infection in a Susceptible Immunocompetent Mouse Model.

Pulmonary infections caused by the group of nontuberculosis mycobacteria (NTM), Mycobacterium avium complex (MAC), are a growing public health concern with incidence and mortality steadily increasing globally. Granulomatous inflammation is the hallmark of MAC lung infection, yet reliable correlates of disease progression, susceptibility, and resolution are poorly defined. Unlike widely used inbred mouse strains, mice that carry the mutant allele at the genetic locus sst1 develop human-like pulmonary tuberculosis featuring well-organized caseating granulomas. We characterized pulmonary temporospatial outcomes of intranasal and left intrabronchial M. avium spp. hominissuis (M.av) induced pneumonia in B6.Sst1S mice, which carries the sst1 mutant allele. We utilized traditional semi-quantitative histomorphological evaluation, in combination with fluorescent multiplex immunohistochemistry (fmIHC), whole slide imaging, and quantitative digital image analysis. Followingintrabronchiolar infection with the laboratory M.av strain 101, the B6.Sst1S pulmonary lesions progressed 12–16 weeks post infection (wpi), with plateauing and/or resolving disease by 21 wpi. Caseating granulomas were not observed during the study. Disease progression from 12–16 wpi was associated with increased acid-fast bacilli, area of secondary granulomatous pneumonia lesions, and Arg1+ and double positive iNOS+/Arg1+ macrophages. Compared to B6 WT, at 16 wpi, B6.Sst1S lungs exhibited an increased area of acid-fast bacilli, larger secondary lesions with greater Arg1+ and double positive iNOS+/Arg1+ macrophages, and reduced T cell density. This morphomolecular analysis of histologic correlates of disease progression in B6.Sst1S could serve as a platform for assessment of medical countermeasures against NTM infection.

POS0145 CLINICAL RESPONSE TO RITUXIMAB IS ASSOCIATED WITH PREVENTION OF B-CELL DRIVEN SALIVARY GLAND INFLAMMATION AND EPITHELIAL RESTORATION AS REVEALED BY MOLECULAR PATHOLOGY: RESULTS FROM THE TRACTISS TRIAL IN PRIMARY SJOGREN’S SYNDROME

BackgroundThe TRial for Anti-B-Cell Therapy In patients with pSS (TRACTISS) is the largest multi-centre, placebo-controlled, phase-III trial with the administration of 2 cycles of Rituximab (RTX) or placebo at week 0 and 24, with trial clinical endpoints at week 48. Despite the primary endpoints (30% reduction in fatigue or oral dryness) were not met, RTX treated patients showed an improvement in secondary endpoints, such as unstimulated whole salivary flow (UWSF), and salivary gland (SG) total ultrasound score1,2. Additionally, recent post-hoc analysis of TRACTISS using novel CRESS composite endpoints3, highlighted a significantly increased response rate in the RTX vs placebo arm.ObjectivesTo perform the first longitudinal analysis of matched transcriptomic and histological data of SG biopsies of pSS patients treated with RTX vs placebo at 3 time points, over 48 weeks, from the TRACTISS cohort, in order to identify mechanisms of response/resistance to B cell depletion.Methods29 pSS patients randomised to RTX or placebo arm consented for labial SG biopsies at week 0, 16 and 48. Patients received two 1000mg cycles of RTX or placebo at week 0 and 24. SG focus score, inflammatory aggregate area fraction, B-cells (CD20+), T-cells (CD3+), follicular dendritic cells (FDCs) (CD21+) and plasma cells (CD138+) density were assessed using quantitative digital image analysis. RNA sequencing with deconvolution and pathway analysis was performed to identify genes signatures and consensus gene modules as biomarkers of disease evolution and response/resistance to therapy.ResultsPlacebo-treated SGs showed worsening of SG inflammation highlighted by the increment of aggregate size, B-cell density, development of new FDC networks, and a higher ectopic GC prevalence over 48 weeks, compared to RTX-treated patients. No difference in focus score, total T-cell and plasma cell infiltration was observed. RTX downregulated genes involved in immune cell recruitment and inflammatory aggregate organisation (e.g. CXCL13, CCR7 and PDCD1). Gene signature-based analysis of 35 immune cell types using XCell highlighted how RTX blocked class-switched and memory-B-cells accumulation in SGs over 48 weeks. Pathway analyses confirmed the downregulation of leukocyte migration, MHC-II antigen presentation, and T-cell co-stimulation immunological pathways, such as the CD40 receptor complex pathway. Among RTX-treated patients, only CRESS-responders demonstrated prevention of worsening B cell-driven molecular pathology signatures over time and a significant improvement in UWSF, in parallel with the upregulation of molecular pathways associated to SG restoration of the glandular epithelium. None of the above effects were observed at week 16 after the first RTX cycle.ConclusionTwo RTX infusions repeated at week 24 exerted beneficial effects on labial SG inflammatory infiltration in pSS by downregulating genes involved in immune cell recruitment, activation and organisation in ectopic GCs. Conversely, all the above parameters showed significant evolution in placebo treated patients over 48 weeks demonstrating progression of SG immunopathology. Clinical responders to RTX based on CRESS response criteria were characterised by preservation of exocrine function which appear driven by SG epithelial restoration.

Super-Resolved Segmentation of X-ray Images of Carbonate Rocks Using Deep Learning

Reliable quantitative analysis of digital rock images requires precise segmentation and identification of the macroporosity, sub-resolution porosity, and solid\\mineral phases. This is highly emphasized in heterogeneous rocks with complex pore size distributions such as carbonates. Multi-label segmentation of carbonates using classic segmentation methods such as multi-thresholding is highly sensitive to user bias and often fails in identifying low-contrast sub-resolution porosity. In recent years, deep learning has introduced efficient and automated algorithms that are capable of handling hard tasks with precision comparable to human performance, with application to digital rocks super-resolution and segmentation emerging. Here, we present a framework for using convolutional neural networks (CNNs) to produce super-resolved segmentations of carbonates rock images for the objective of identifying sub-resolution porosity. The volumes used for training and testing are based on two different carbonates rocks imaged in-house at low and high resolutions. We experiment with various implementations of CNNs architectures where super-resolved segmentation is obtained in an end-to-end scheme and using two networks (super-resolution and segmentation) separately. We show the capability of the trained model of producing accurate segmentation by comparing multiple voxel-wise segmentation accuracy metrics, topological features, and measuring effective properties. The results underline the value of integrating deep learning frameworks in digital rock analysis.

Quantitative analysis of breast cancer tissue composition and associations with tumor subtype

The tumor microenvironment is an important determinant of breast cancer progression, but standard methods for describing the tumor microenvironment are lacking. Measures of microenvironment composition such as stromal area and immune infiltrate are labor-intensive and few large studies have systematically collected this data. However, digital histologic approaches are becoming more widely available, allowing high-throughput, quantitative estimation. We applied such methods to tissue microarrays of tumors from 1687 women (mean 4 cores per case) in the Carolina Breast Cancer Study Phase 3. Tumor composition was quantified as percentage of epithelium, stroma, adipose, and lymphocytic infiltrate (with the latter as presence/absence using a ≥1% cutoff). Composition proportions and presence/absence were evaluated in association with clinical and molecular features of breast cancer (intrinsic subtype and RNA-based risk of recurrence [ROR] scores) using multivariable linear and logistic regression. Lower stromal content was associated with aggressive tumor phenotypes, including triple-negative (31.1% vs. 41.6% in HR+/HER2-; RFD [95% CI]: -10.5%, [-13.1, -7.9]), Basal-like subtypes (29.0% vs. 44.0% in Luminal A; RFD [95% CI]: -14.9%, [-17.8, -12.0]), and high RNA-based PAM50 ROR scores (27.6% vs. 48.1% in ROR low; RFD [95% CI]: -20.5%, [24.3, 16.7]), after adjusting for age and race. HER2+ tumors also had lower stromal content, particularly among RNA-based HER2-enriched (35.2% vs. 44.0% in Luminal A; RFD [95% CI]: -8.8%, [-13.8, -3.8]). Similar associations were observed between immune infiltrate and tumor phenotypes. Quantitative digital image analysis of the breast cancer microenvironment showed significant associations with demographic characteristics and biological indicators of aggressive behavior.

SpatialTIME and iTIME: R package and Shiny application for visualization and analysis of immunofluorescence data.

SummaryMultiplex immunofluorescence (mIF) staining combined with quantitative digital image analysis is a novel and increasingly used technique that allows for the characterization of the tumor immune microenvironment (TIME). Generally, mIF data is used to examine the abundance of immune cells in the TIME; however, this does not capture spatial patterns of immune cells throughout the TIME, a metric increasingly recognized as important for prognosis. To address this gap, we developed an R package spatialTIME that enables spatial analysis of mIF data, as well as the iTIME web application that provides a robust but simplified user interface for describing both abundance and spatial architecture of the TIME. The spatialTIME package calculates univariate and bivariate spatial statistics (e.g. Ripley’s K, Besag’s L, Macron’s M and G or nearest neighbor distance) and creates publication quality plots for spatial organization of the cells in each tissue sample. The iTIME web application allows users to statistically compare the abundance measures with patient clinical features along with visualization of the TIME for one tissue sample at a time.Availability and implementationspatialTIME is implemented in R and can be downloaded from GitHub (https://github.com/FridleyLab/spatialTIME) or CRAN. An extensive vignette for using spatialTIME can also be found at https://cran.r-project.org/web/packages/spatialTIME/index.html. iTIME is implemented within a R Shiny application and can be accessed online (http://itime.moffitt.org/), with code available on GitHub (https://github.com/FridleyLab/iTIME).Supplementary information Supplementary data are available at Bioinformatics online.

COMPLEX OF MATHEMATICAL MODELS AND METHODS TO CALCULATE PRESSURE EFFECT ON SULFIDE DISTRIBUTION IN STEEL

Primary objective is to develop computational method to analyze digital pictures of sulfide prints, helping obtain qualitative image characteristics, and to formulate mathematical model of the distribution of sulphide inclusions to determine specific features of the pressure effect on the macrostructure formation of carbon steel castings flooded into the uncooled mold.&#x0D; The research was carried out using images of sulfide prints of templates cut of steel cylindrical castings; L500 steel was applied. The castings result from industrial tests of a method of gas-dynamic effect on the fusion in the foundry forms under the conditions of a casthouse of Dnipropetrovsk aggregate plant PJSC. Digital pictures of sulfide prints, obtained in terms of the increased rate of gas pressure and maximum pressure, were binarized; defective fra gments were removed; and zoning took place. The developed computational method has been applied for fragments of images, representing different zones; data arrays have been received containing sizes and amounts of inclusions in the fragment.&#x0D; The developed computational method to analyze digital images of sulfide prints has been implemented. ASImprints software support has helped obtain qualitative characteristics of images; namely, distribution of amount of the certain-size sulfide inclusions. &#x0D; The computational method to analyze digital images of sulfide prints has made it possible to study the set of patterns of sulfide prints. The dependences have been obtained, describing specific features of sulfide inclusion distribution while varying gas-dynamic pressure method in terms of fusion in the casting form. It has been demonstrated that the distribution describes effectively the power-series distribution to compare with the exponential one. Mathematical model of the power-series distribution parameter dependence upon pressure has been developed. Deviation of the distribution parameters in terms of the experimental values and the model values has been evaluated. &#x0D; The research demonstrates the ways to apply an algorithm of simple recursive casting for quantitative analysis of digital images of sulfide prints. Use of ASImprints, being software implementation of the computational method to analyze digital images of sulfide prints making it possible to obtain qualitative characteristics of images, has helped identify that the increased pressure within a casting-device for gas injection system results in the increased specific amount of inclusions and the decreased specific zone of sulfide inclusions respectively. It has been defined that exponential function describes reliably the nature of sulfide inclusion distribution in the digital image of sulfide print. The research has demonstrated that fragments of a sulfide print, belonging to one zone, are statistically homogeneous. Thus, it is possible to analyze quantitively digital image zone of a sulfide print on its fragment. Mathematical model of dependence of sulfide inclusion distribution in carbon-steel castings in terms of gas-dynamic effect on fusion solidifying in a mold has been developed. The model may be applied to predict sulfide inclusion distribution within the selected zones of cross section of the cylindrical castings solidifying in the uncooled mold in terms of the preset mode of gas-dynamic effect.&#x0D; Keywords: gas-dynamic effect, pressure, solidification, casting, steel, 35 Л, mold, macrostructure, sulfides, inclusions, template, sulfide print, distribution, polynomial, parameters, prediction, software implementation, ASImprints

Development of a multiplex immuno-oncology biomarker and digital pathology workflow for assessment of urothelial carcinoma

BackgroundImmune checkpoint inhibitors (ICI) therapies have demonstrated significant benefit in the treatment of many tumors including high grade urothelial cancer (HGUC) of the bladder. However, variability in patients’ clinical responses highlights the need for biomarkers to aid patient stratification. ICI relies on an intact host immune response. In this context, we hypothesize that key players in the antitumor immune response such as markers of activated cytotoxic T lymphocytes (CD8, granzyme-B) and immune suppression (FOXP3) may help to identify patients who will derive the greatest therapeutic benefit from ICI. A major obstacle for deployment of such a strategy is the limited quantities of tumor-derived biopsy material. Therefore, in this technical study, we develop a multiplex biomarker with digital workflow. We explored the (1) concordance of conventional single stain results using digital image analysis, and (2) agreement between digital scoring versus manual analysis. Methods(1) For concordance study of single and multiplex stains, triplicate core tissue microarrays of 207 muscle invasive, HGUC of bladder had sequential 4-micron sections cut and stained with CD8, FOXP3 and granzyme-B. An inhouse developed tri-chromogen multiplex immunohistochemistry (m-IHC) assay consisting of CD8 (green), granzyme B (brown), and FOXP3 (red) was used to stain the next sequential tissue section. (2) Agreement between manual and digital analysis was performed on 19 whole slide sections of HGUC cystectomy specimens. All slides were scanned using Aperio ScanScope AT Digital Scanner at 40X. Quantitative digital image analysis was performed using QuPath version 0.2.3 open-source software. Scores from triplicate cores were averaged for each HGUC specimen for each marker. Intraclass correlation coefficients were used to compare percent positive cells between the single- and multi-plex assays. Lin’s concordance correlation coefficients were used for manual versus digital analysis. Results and conclusionsm-IHC offers significant advantages in characterizing the host immune microenvironment particularly in limited biopsy tissue material. Utilizing a digital image workflow resulted in significant concordance between m-IHC and individual single stains (p < 0.001 for all assessments). Moderate to good agreements were achieved between manual and digital scoring. Our technical work demonstrated potential uses of multiplex marker in assessing the host immune status and could be used in conjunction with PD-L1 as a predictor of response to ICI therapy.

Novel quantitative digital image analysis methodology for assessment of inflammatory changes in MRI data in a post-hoc analysis of data acquired from a phase IIb study of baricitinib in patients with active rheumatoid arthritis

PurposeTo evaluate a novel quantitative methodology to assess inflammatory changes in magnetic resonance imaging (MRI) data from patients with rheumatoid arthritis (RA) and the impact of image quality on imaging outcomes compared to the RA Magnetic Resonance Imaging Score (RAMRIS). MethodsThree-dimensional, T1-weighted, fat-suppressed MRI sequences of the hand/wrist before and after intravenous Gadolinium contrast from patients with RA in a placebo-controlled clinical trial (NCT01185353) were re-evaluated post hoc. The methodology was integrated into proprietary software (DYNAMIKA®) and assessed inflammation through pixelated measurements of the contrast-enhancing (inflammatory) volume. A semi-automatic approach outlined contrast-enhancing synovial tissue in the wrist and second to fifth metacarpophalangeal joints with a rough region of interest (ROI); quantitative imaging biomarkers were generated by means of quantitative total volume of inflammation and quantitative degree of inflammation relative to the signal in a 1 cm in diameter ROI in the center of the thenar or lumbrical muscle for internal reference. The time from Gadolinium injection to finalization of the post-contrast images was calculated from the images’ Digital Imaging and Communications in Medicine header. An experienced reader graded image quality as poor, acceptable, or good. ResultsResults from this quantitative methodology, especially when excluding images with poor quality scores (14–32%), provided a more pronounced and monotonically increasing dose-response than the original RAMRIS results on synovitis and osteitis. ConclusionsThis computer-aided quantitative scoring method provided continuous measures of inflammatory changes relative to muscle and may be more sensitive and interpretable concerning dose/response separation between RA treatment groups.

Characterization of in vitro 3D cultures.

Over the past decade, 3D culture models of human and animal cells have found their way into tissue differentiation, drug development, personalized medicine and tumour behaviour studies. Embryoid bodies (EBs) are in vitro 3D cultures established from murine pluripotential stem cells, whereas tumoroids are patient-derived in vitro 3D cultures. This thesis aims to describe a new implication of an embryoid body model and to characterize the patient-specific microenvironment of the parental tumour in relation to tumoroid growth rate. In this thesis, we described a high-throughput monitoring method, where EBs are used as a dynamic angiogenesis model. In this model, digital image analysis (DIA) is implemented on immunohistochemistry (IHC) stained sections of the cultures over time. Furthermore, we have investigated the correlation between the genetic profile and inflammatory microenvironment of parental tumours on the in vitro growth rate of tumoroids. The EBs were cultured in spinner flasks. The samples were collected at days 4, 6, 9, 14, 18 and 21, dehydrated and embedded in paraffin. The histological sections were IHC stained for the endothelial marker CD31 and digitally scanned. The virtual whole-image slides were digitally analysed by Visiopharm® software. Histological evaluation showed vascular-like structures over time. The quantitative DIA was plausible to monitor significant increase in the total area of the EBs and an increase in endothelial differentiation. The tumoroids were established from 32 colorectal adenocarcinomas. The in vitro growth rate of the tumoroids was followed by automated microscopy over an 11-day period. The parental tumours were analysed by next-generation sequencing for KRAS, TP53, PIK3CA, SMAD4, MAP2K1, BRAF, FGFR3 and FBXW7 status. The tumoroids established from KRAS-mutated parental tumours showed a significantly higher growth rate compared to their wild-type counterparts. The density of CD3+ T lymphocytes and CD68+ macrophages was calculated in the centre of the tumours and at the invasive margin of the tumours. The high density of CD3+ cells and the low density of CD68+ cells showed a significant correlation with a higher growth rate of the tumoroids. In conclusion, a novel approach for histological monitoring of endothelial differentiation is presented in the stem cell-derived EBs. Furthermore, the KRAS status and density of CD3+ T cells and macrophages in the parental tumour influence the growth rate of the tumoroids. Our results indicate that these parameters should be included when tumoroids are to be implemented in personalized medicine.

Quantitative digital image analysis of somatostatin receptor 2 immunohistochemistry in pancreatic neuroendocrine tumors.

Immunohistochemical analysis of somatostatin receptor 2 (SSTR2) provides important information regarding the potential therapeutic efficacy of somatostatin analogues (SSAs) in patients with neuroendocrine tumors. HER2 scoring has been proposed to interpret SSTR2 immunoreactivity but their reproducibility was relatively low because of its intrinsic subjective nature. Digital image analysis (DIA) has recently been proposed as an objective and more precise method of evaluating immunoreactivity. Therefore, in this study, we used DIA for analyzing SSTR2 immunoreactivity in pancreatic neuroendocrine tumors (PanNETs) to obtain its H score and "(%) strong positive cells" and compared the results with those of manually obtained HER2 scores. Membranous SSTR2 immunoreactivity evaluated by DIA was calculated by two scales as: "Membrane Optical Density" and "Minimum Membrane Completeness". PanNETs with HER2 score of > 2 demonstrated the highest concordance with results of "(%) strong positive cells" obtained by DIA when "Minimum Membrane Completeness" was tentatively set at 80%. The SSTR2 immunoreactivity, evaluated based on all scoring systems, was different between grades G1 and G2 in insulinoma but not in non-functional PanNETs. DIA provided reproducible results of SSTR2 immunoreactivity in PanNETs and yielded important information as to the potential application of SSAs.

Liver Collagen Contents Are Closely Associated with the Severity of Cirrhosis and Posthepatectomy Liver Failure in Patients with Hepatocellular Carcinoma and Child-Pugh Grade A Liver Function.

Hepatocellular carcinoma (HCC) is usually accompanied by different severities of cirrhosis, which is a risk factor for posthepatectomy liver failure (PHLF). Collagen proportional area (CPA) measurements can quantitatively determine the collagen contents of liver tissue. This study explored the impact of CPA on PHLF, and further investigated the correlation between CPA and a non-invasive method, namely cirrhotic severity scoring (CSS), previously proposed by our team. A total of 224 HCC patients with Child-Pugh grade A liver function undergoing hepatectomy between 2017 and 2019 were retrospectively studied. Quantitative digital image analysis of resected liver tissues was used for the CPA measurement. Risk factors for PHLF were subjected to univariate and multivariate analyses, and the correlation between CPA and CSS was analyzed. Overall, 28 (12.5%) patients experienced PHLF. Patients with PHLF had higher CPA values than those without PHLF (p < 0.001). Multivariate analysis showed CPA and extent of hepatectomy to be independent risk factors for PHLF. CPA values were divided into four stages based on their quartiles (C1: < 6.6%; C2: 6.6-10.7%; C3: 10.7-18.0%; C4: ≥ 18.0%). The incidence of PHLF increased with increasing CPA stages (p < 0.001). Furthermore, CSS was significantly correlated with CPA (r = 0.720; p < 0.001). The incidence of PHLF also increased with increasing severity of cirrhosis evaluated by CSS (p < 0.001). In HCC patients with Child-Pugh grade A liver function, cirrhosis could be staged by liver collagen contents, which significantly influenced PHLF. Furthermore, CSS was useful in the preoperative evaluation of cirrhotic severity.

Advance Techniques in Medical Imaging under Big Data Analysis: Covid-19 Images

Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. Accurate segmentation is required for volume determination, 3D rendering, radiation therapy, and surgery planning. In medical images, segmentation has traditionally been done by human experts. Substantial computational and storage requirements become especially acute when object orientation and scale have to be considered. Therefore, automated or semi-automated segmentation techniques are essential if these software applications are ever to gain widespread clinical use. Many methods have been proposed to detect and segment 2D shapes, most of which involve template matching. Advanced segmentation techniques called Snakes or active contours have been used, considering deformable models or templates. The main purpose of this work is to apply segmentation techniques for the definition of 3D organs (anatomical structures) when big data information has been stored and must be organized by the doctors for medical diagnosis. The processes would be implemented in the CT images from patients with COVID-19.

Intratumoral budding and automated CD8-positive T-cell density in pretreatment biopsies can predict response to neoadjuvant therapy in rectal adenocarcinoma

Tumor budding and CD8-positive (+) T-cells are recognized as prognostic factors in colorectal adenocarcinoma. We assessed CD8+ T-cell density and intratumoral budding in pretreatment rectal cancer biopsies to determine if they are predictive biomarkers for response to neoadjuvant therapy and survival. Pretreatment biopsies of locally advanced rectal adenocarcinoma from 117 patients were evaluated for CD8+ T-cell density using automated quantitative digital image analysis and for intratumoral budding and correlated with clinicopathological variables on postneoadjuvant surgical resection specimens, response to neoadjuvant therapy, and survival. Patients with high CD8+ T-cell density (≥157 per mm2) on biopsy were significantly more likely to exhibit complete/near complete response to neoadjuvant therapy (66% vs. 33%, p = 0.001) and low tumor stage (0 or I) on resection (62% vs. 30%, p = 0.001) compared with patients with low CD8+ T-cell density. High CD8+ T-cell density was an independent predictor of response to neoadjuvant therapy with a 2.63 higher likelihood of complete response (95% CI 1.04–6.65, p = 0.04) and a 3.66 higher likelihood of complete/near complete response (95% CI 1.60–8.38, p = 0.002). The presence of intratumoral budding on biopsy was significantly associated with a reduced likelihood of achieving complete/near complete response to neoadjuvant therapy (odds ratio 0.36, 95% CI 0.13–0.97, p = 0.048). Patients with intratumoral budding on biopsy had a significantly reduced disease-free survival compared with patients without intratumoral budding (5-year survival 39% vs 87%, p < 0.001). In the multivariable model, the presence of intratumoral budding on biopsy was associated with a 3.35-fold increased risk of tumor recurrence (95% CI 1.25–8.99, p = 0.02). In conclusion, CD8+ T-cell density and intratumoral budding in pretreatment biopsies of rectal adenocarcinoma are independent predictive biomarkers of response to neoadjuvant therapy and intratumoral budding associates with patient survival. These biomarkers may be helpful in selecting patients who will respond to neoadjuvant therapy and identifying patients at risk for recurrence.

Application of digital image analysis on histological images of a murine embryoid body model for monitoring endothelial differentiation

The in vitro 3D model established from murine pluripotential stem cells (i.e., embryoid bodies (EBs)) is a dynamic model for endothelial differentiation. The aim of the present study was to investigate whether digital image analysis (DIA) can be applied on histological sections of EBs in order to quantify endothelial differentiation over time. The EBs were established in suspension cultures for 21 days in three independent replicate experiments. At day 4, 6, 9, 14, 18, and 21, the EBs were fixed in formaldehyde, embedded in paraffin and immunohistochemically (IHC) stained for CD31. The IHC-stained slides were digitally scanned and analysed using the Visiopharm® Quantitative Digital Pathology software Oncotopix™. The EBs developed CD31+ vascular-like structures during their differentiation. The quantitative DIA of the EBs showed that the log10 values of the relative CD31+ areas increased from −0.574 ± 0.470 (mean ± SD) at day 4 to 0.093 ± 0.688 (mean ± SD) at day 21 (p < 0.001). The approach presented in this study is a fast, quantitative and reproducible alternative method for an otherwise time-consuming and observer-dependent histological investigation. The future perspectives for such a system would be implementation of a modified version of the method on different 3D cultures and IHC markers.

Quantitative patterns of motor cortex proteinopathy across ALS genotypes

Degeneration of the primary motor cortex is a defining feature of amyotrophic lateral sclerosis (ALS), which is associated with the accumulation of microscopic protein aggregates in neurons and glia. However, little is known about the quantitative burden and pattern of motor cortex proteinopathies across ALS genotypes. We combined quantitative digital image analysis with multi-level generalized linear modelling in an independent cohort of 82 ALS cases to explore the relationship between genotype, total proteinopathy load and cellular vulnerability to aggregate formation. Primary motor cortex phosphorylated (p)TDP-43 burden and microglial activation were more severe in sporadic ALS-TDP disease than C9-ALS. Oligodendroglial pTDP-43 pathology was a defining feature of ALS-TDP in sporadic ALS, C9-ALS and ALS with OPTN, HNRNPA1 or TARDBP mutations. ALS-FUS and ALS-SOD1 showed less cortical proteinopathy in relation to spinal cord pathology than ALS-TDP, where pathology was more evenly spread across the motor cortex-spinal cord axis. Neuronal pTDP-43 aggregates were rare in GAD67+ and Parvalbumin+ inhibitory interneurons, consistent with predominant accumulation in excitatory neurons. Finally, we show that cortical microglia, but not astrocytes, contain pTDP-43. Our findings suggest divergent quantitative, genotype-specific vulnerability of the ALS primary motor cortex to proteinopathies, which may have implications for our understanding of disease pathogenesis and the development of genotype-specific therapies.

Clinical Application of Image Analysis in Pathology.

Quantitative biomarkers are key prognostic and predictive factors in the diagnosis and treatment of cancer. In the clinical laboratory, the majority of biomarker quantitation is still performed manually, but digital image analysis (DIA) methods have been steadily growing and account for around 25% of all quantitative immunohistochemistry (IHC) testing performed today. Quantitative DIA is primarily employed in the analysis of breast cancer IHC biomarkers, including estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2/neu; more recently clinical applications have expanded to include human epidermal growth factor receptor 2/neu in gastroesophageal adenocarcinomas and Ki-67 in both breast cancer and gastrointestinal and pancreatic neuroendocrine tumors. Evidence in the literature suggests that DIA has significant benefits over manual quantitation of IHC biomarkers, such as increased objectivity, accuracy, and reproducibility. Despite this fact, a number of barriers to the adoption of DIA in the clinical laboratory persist. These include difficulties in integrating DIA into clinical workflows, lack of standards for integrating DIA software with laboratory information systems and digital pathology systems, costs of implementing DIA, inadequate reimbursement relative to those costs, and other factors. These barriers to adoption may be overcome with international standards such as Digital Imaging and Communications in Medicine (DICOM), increased adoption of routine digital pathology workflows, the application of artificial intelligence to DIA, and the emergence of new clinical applications for DIA.